Instructions to use superb/wav2vec2-base-superb-sid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use superb/wav2vec2-base-superb-sid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="superb/wav2vec2-base-superb-sid")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("superb/wav2vec2-base-superb-sid") model = AutoModelForAudioClassification.from_pretrained("superb/wav2vec2-base-superb-sid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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language: en
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datasets:
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- librispeech_asr
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tags:
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- audio
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- audio-classification
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widget:
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- label: Librispeech sample 1
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src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
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- label: Librispeech sample 2
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src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
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